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Bert-Ram Sah

Researcher at University of Zurich

Publications -  26
Citations -  717

Bert-Ram Sah is an academic researcher from University of Zurich. The author has contributed to research in topics: PET-CT & Perfusion scanning. The author has an hindex of 16, co-authored 24 publications receiving 569 citations. Previous affiliations of Bert-Ram Sah include University of Bern.

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Diagnostic Performance of 18F-FDG-PET/CT in Vascular Graft Infections

TL;DR: The diagnostic accuracy of FDG-PET/CT in the detection of aortic graft infection is high and a newly introduced five point visual grading score and early imaging prior to antimicrobial treatment may further improve the diagnostic accuracy.
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Benefit of 18F-fluorocholine PET imaging in parathyroid surgery

TL;DR: 18F-fluorocholine PET imaging is a highly accurate method to detect parathyroid adenomas even in case of previous localization failure by other imaging examinations, and is encouraged to use, where ultrasound fails to detect an adenoma.
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Dosimetry and First Clinical Evaluation of the New 18F-Radiolabeled Bombesin Analogue BAY 864367 in Patients with Prostate Cancer

TL;DR: BAY 864367, a novel 18F-labeled bombesin tracer, was successfully investigated in a first-in-man clinical trial of PCa and showed favorable dosimetric values, indicating the application was safe and well tolerated.
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Computed tomographic perfusion imaging for the prediction of response and survival to transarterial radioembolization of liver metastases.

TL;DR: Arterial perfusion of liver metastases, as determined by pretreatment CT perfusion imaging, enables prediction of short-term morphologic response and 1-year survival after transarterial radioembolization (TARE).
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Clinical evaluation of a block sequential regularized expectation maximization reconstruction algorithm in 18F-FDG PET/CT studies.

TL;DR: The BSREM reconstruction algorithm showed a relevant improvement compared with OSEM reconstruction in PET/CT studies in all evaluated categories and might be used in clinical routine in conjunction with TOF to achieve better/higher image quality and lesion detectability.